We also evaluate the results on the smaller dataset of [1]} and compare to the state of the art.
As our model requires a significant amount of data we initially learn on a large dataset.
KITTI makes available a considerable number of LiDAR scans with different scenarios, but all correspond to outdoor road environments.
To apply our approach to smaller datasets acquired in very different environments, a fine-tuning process is applied using the pre-trained model on the KITTI dataset.
This allows to obtain much better results compared to re-training on such a small dataset and shows the importance of epistemic uncertainty as an indicator of the performances of a model on unseen data.
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